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302 ENTERPRISE INFORMATION SYSTEMS VI<br />

based on established psychological studies, as well<br />

as empirical analysis of actual video footage from<br />

human-computer interaction sessions and human-tohuman<br />

dialogues. The results of the synthesis process<br />

can then be applied to avatars, so as to convey<br />

the communicated messages more vividly than plain<br />

textual information or simply to make interaction<br />

more lifelike.<br />

2 MPEG-4 REPRESENTATION<br />

In the framework of MPEG-4 standard, parameters<br />

have been specified for Face and Body Animation<br />

(FBA) by defining specific Face and Body nodes in<br />

the scene graph. The goal of FBA definition is the<br />

animation of both realistic and cartoonist characters.<br />

Thus, MPEG-4 has defined a large set of parameters<br />

and the user can select subsets of these parameters<br />

according to the application, especially for the body,<br />

for which the animation is much more complex. The<br />

FBA part can be also combined with multimodal<br />

input (e.g. linguistic and paralinguistic speech analysis).<br />

2.1 Facial Animation<br />

MPEG-4 specifies 84 feature points on the neutral<br />

face, which provide spatial reference for FAPs definition.<br />

The FAP set contains two high-level parameters,<br />

visemes and expressions. In particular, the Facial<br />

Definition Parameter (FDP) and the Facial Animation<br />

Parameter (FAP) set were designed in the<br />

MPEG-4 framework to allow the definition of a facial<br />

shape and texture, eliminating the need for<br />

specifying the topology of the underlying geometry,<br />

through FDPs, and the animation of faces reproducing<br />

expressions, emotions and speech pronunciation,<br />

through FAPs. By monitoring facial gestures corresponding<br />

to FDP and/or FAP movements over time,<br />

it is possible to derive cues about user’s expressions<br />

and emotions. Various results have been presented<br />

regarding classification of archetypal expressions of<br />

faces, mainly based on features or points mainly<br />

extracted from the mouth and eyes areas of the<br />

faces. These results indicate that facial expressions,<br />

possibly combined with gestures and speech, when<br />

the latter is available, provide cues that can be used<br />

to perceive a person’s emotional state.<br />

The second version of the standard, following<br />

the same procedure with the facial definition and<br />

animation (through FDPs and FAPs), describes the<br />

anatomy of the human body with groups of distinct<br />

tokens, eliminating the need to specify the topology<br />

of the underlying geometry. These tokens can then<br />

be mapped to automatically detected measurements<br />

and indications of motion on a video sequence, thus,<br />

they can help to estimate a real motion conveyed by<br />

the subject and, if required, approximate it by means<br />

of a synthetic one.<br />

2.2 Body Animation<br />

In general, an MPEG body is a collection of<br />

nodes. The Body Definition Parameter (BDP) set<br />

provides information about body surface, body<br />

dimensions and texture, while Body Animation<br />

Parameters (BAPs) transform the posture of the<br />

body. BAPs describe the topology of the human<br />

skeleton, taking into consideration joints’ limitations<br />

and independent degrees of freedom in the<br />

skeleton model of the different body parts.<br />

2.2.1 BBA (Bone Based Animation)<br />

The MPEG-4 BBA offers a standardized interchange<br />

format extending the MPEG-4 FBA (Preda &<br />

Preteux, 2002). In BBA the skeleton is a hierarchical<br />

structure made of bones. In this hierarchy every<br />

bone has one parent and can have as children other<br />

bones, muscles or 3D objects. For the movement of<br />

every bone we have to define the influence of this<br />

movement to the skin of our model, the movement<br />

of its children and the related inverse kinematics.<br />

3 EMOTION REPRESENTATION<br />

The obvious goal for emotion analysis applications<br />

is to assign category labels that identify emotional<br />

states. However, labels as such are very poor descriptions,<br />

especially since humans use a daunting<br />

number of labels to describe emotion. Therefore we<br />

need to incorporate a more transparent, as well as<br />

continuous representation, that matches closely our<br />

conception of what emotions are or, at least, how<br />

they are expressed and perceived.<br />

Activation-emotion space (Whissel, 1989) is a<br />

representation that is both simple and capable of<br />

capturing a wide range of significant issues in emotion.<br />

It rests on a simplified treatment of two key<br />

themes:<br />

�� Valence: The clearest common element of emotional<br />

states is that the person is materially influenced<br />

by feelings that are ‘valenced’, i.e.<br />

they are centrally concerned with positive or<br />

negative evaluations of people or things or<br />

events. The link between emotion and valencing<br />

is widely agreed<br />

�� Activation level: Research has recognised that<br />

emotional states involve dispositions to act in<br />

certain ways. A basic way of reflecting that

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